Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence

Bangfeng Wang; Yiwei Li; Mengfan Zhou; Yulong Han; Mingyu Zhang; Zhaolong Gao; Zetai Liu; Peng Chen; Wei Du; Xingcai Zhang; Xiaojun Feng; Bi-Feng Liu

doi:10.1038/s41467-023-36017-x

Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence

Nat Commun. 2023 Mar 11;14(1):1341. doi: 10.1038/s41467-023-36017-x.

Authors

Bangfeng Wang^#¹, Yiwei Li^#¹, Mengfan Zhou¹, Yulong Han², Mingyu Zhang¹, Zhaolong Gao¹, Zetai Liu¹, Peng Chen¹, Wei Du¹, Xingcai Zhang³, Xiaojun Feng⁴, Bi-Feng Liu⁵

Affiliations

¹ The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
² School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.
³ School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA. 24212602@qq.com.
⁴ The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China. xfeng@mail.hust.edu.cn.
⁵ The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China. bfliu@mail.hust.edu.cn.

^# Contributed equally.

Abstract

The frequent outbreak of global infectious diseases has prompted the development of rapid and effective diagnostic tools for the early screening of potential patients in point-of-care testing scenarios. With advances in mobile computing power and microfluidic technology, the smartphone-based mobile health platform has drawn significant attention from researchers developing point-of-care testing devices that integrate microfluidic optical detection with artificial intelligence analysis. In this article, we summarize recent progress in these mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms. We document the application of mobile health platforms in terms of the detection objects, including molecules, viruses, cells, and parasites. Finally, we discuss the prospects for future development of mobile health platforms.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Artificial Intelligence
Humans
Microfluidics*
Point-of-Care Testing
Smartphone*
Software